Generative recommender systems: A comprehensive survey on model, framework, and application

Yuqiu Zhao, Chaohong Tan, Lei Shi, Yan Zhong, Feifei Kou, Pengfei Zhang, Wei Chen, Chen Ma

Abstract: Highlights•Provides a comprehensive analysis of generative recommender systems from an architectural perspective, covering mainstream generative models.•Summarizes metadata sources, representation learning, and information fusion approaches.•Analyzes core challenges and effective technical solutions in industrial scenarios.•Identifies remaining bottlenecks and future directions.

External IDs:doi:10.1016/j.inffus.2025.103919